1. Field of the Invention
The present invention is directed in general to the field of information processing. In one aspect, the present invention relates to a system and method for improving efficiency in communication networks employing adaptive antenna systems.
2. Description of the Related Art
Wireless communication systems transmit and receive signals within a designated electromagnetic frequency spectrum, but the capacity of the electromagnetic frequency spectrum is limited. As the demand for wireless communication systems continues to expand, there are increasing challenges to improve spectrum usage efficiency. To address this problem, many communication networks have been designed to support adaptive antenna systems (AAS) to improve the communication capacity of the network. Adaptive antenna systems comprise multiple antennas at the transmitting and/or the receiving side of the communication link. In communication networks supporting AAS, the signals are processed adaptively to exploit the spatial dimension of the communication channel.
FIG. 1 depicts a wireless communication system 100 in which a transmitter 102 having a single antenna or an array of antennas 106 communicates with receiver 104 having a single antenna or an array of antennas 108. The communication system 100 may be any type of wireless communication system including, but not limited to, a Multiple Input, Multiple Output (MIMO) system, a Space Division Multiple Access (SDMA) system, a Code Division Multiple Access (CDMA) system, an Orthogonal Frequency Division Multiplexing (OFDM) system, or an Orthogonal Frequency Division Multiple Access (OFDMA) system. In the communication system 100, the transmitter 102 may act as a base station, while the receiver 104 acts as a subscriber station, which can be virtually any type of wireless one-way or two-way communication device such as a cellular telephone, wireless equipped computer system, and wireless personal digital assistant. The receiver/subscriber station 104 can also transmits signals which are received by the transmitter/base station 102. The signals communicated between transmitter 102 and receiver 104 can include voice, data, electronic mail, video, and other data, voice, and video signals. In operation, the transmitter 102 transmits a signal data stream (e.g., signal s1) through one or more antennas 106 and over a channel H1 to a receiver 104, which combines the received signal from one or more receive antennas 108 to reconstruct the transmitted data. To transmit the signal vector s1, the transmitter 102 prepares a transmission signal, represented by the vector x1, for the signal s1. (Note: lower case bold variables indicate vectors and upper case BOLD variables indicate matrices). The transmission signal vector x1 is transmitted via a channel represented by a channel matrix H1, and is received at the receiver 104 as a receive signal vector y1=H1x1+n1 (where n represents co-channel interference or noise). The channel matrix H1 represents a channel gain between the transmitter antenna array 106 and the subscriber station antenna array 108. Thus, the channel matrix H1 can be represented by a k×N matrix of complex coefficients, where N is the number of antennas in the transmitter/base station antenna array 106 and k is the number of antennas in the receiver/subscriber station antenna array 108. The value of k can be unique for each receiver/subscriber station. As will be appreciated, the channel matrix H1 can instead be represented by a N×k matrix of complex coefficients, in which case the matrix manipulation algorithms are adjusted accordingly so that, for example, the right singular vector calculation on a k×N channel matrix becomes a left singular vector calculation on a N×k channel matrix. The coefficients of the channel matrix H1 depend, at least in part, on the transmission characteristics of the medium, such as air, through which a signal is transmitted. A variety of methods may be used at the receiver to determine the channel matrix H1 coefficients, such as transmitting a known pilot signal to a receiver so that the receiver, knowing the pilot signal, can estimate the coefficients of the channel matrix H1 using well-known pilot estimation techniques. Alternatively, when the channel between the transmitter and receiver are reciprocal in both directions, the actual channel matrix H1 is known to the receiver and may also be known to the transmitter.
Communication networks that support AAS do not necessarily provide AAS support in all of the cells of the network. When a subscriber set is operating in a non-AAS cell, it must scan all allocated frequencies to decode channel parameters. If, however, the subscriber set is in an AAS cell, it cannot receive channel parameters and, therefore, must scan all allocated frequencies to decode AAS parameters. Currently, subscribers scan all allocated frequencies to attempt to decode both channel parameters and AAS parameters, even though only one of those sets of parameters is relevant based on the position of the subscriber set. Therefore, the subscriber set unnecessarily consumes significant processing resources. It is apparent, therefore, that there is a need for an improved system and method for scanning allocated frequencies to decode channel parameters and/or AAS parameters in communication networks that support AAS.
Further limitations and disadvantages of conventional processes and technologies will become apparent to one of skill in the art after reviewing the remainder of the present application with reference to the drawings and detailed description which follow.
It will be appreciated that for simplicity and clarity of illustration, elements illustrated in the drawings have not necessarily been drawn to scale. For example, the dimensions of some of the elements are exaggerated relative to other elements for purposes of promoting and improving clarity and understanding. Further, where considered appropriate, reference numerals have been repeated among the drawings to represent corresponding or analogous elements.